IDEAS home Printed from https://ideas.repec.org/p/ecb/ecbsps/201614.html
   My bibliography  Save this paper

Estimating gross value added volumes and prices by institutional sector

Author

Listed:
  • Kavonius, Ilja Kristian
  • Wieland, Elisabeth

Abstract

Integrated quarterly sector accounts (QSA) provide an analytical tool to understand the generation, allocation and use of income for all institutional sectors in the economy. They also provide a tool to analyse production from a sectoral point of view instead of an industry point of view. However, since QSA are published in current prices only, sectoral volume and price measures are lacking as an important toolkit for economic analysis and forecasting, notably in the case of gross value added. This paper introduces a methodology to estimate sectoral price and volume measures for euro area value added at a quarterly frequency and provides a comparison of alternative estimation methods. It presents a benchmark method which yields robust estimates of sectoral volumes and prices in the euro area. JEL Classification: C33, C82, E01, E30

Suggested Citation

  • Kavonius, Ilja Kristian & Wieland, Elisabeth, 2016. "Estimating gross value added volumes and prices by institutional sector," Statistics Paper Series 14, European Central Bank.
    • Handle: RePEc:ecb:ecbsps:201614
    as

    Download full text from publisher

    File URL: https://www.ecb.europa.eu//pub/pdf/scpsps/ecbsp14.en.pdf
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Richard Stone & D. G. Champernowne & J. E. Meade, 1942. "The Precision of National Income Estimates," The Review of Economic Studies, Review of Economic Studies Ltd, vol. 9(2), pages 111-125.
    2. Zlatina Balabanova & Ruben van der Helm, 2015. "Enhancing euro area capital stock estimates," IFC Bulletins chapters, in: Bank for International Settlements (ed.), Indicators to support monetary and financial stability analysis: data sources and statistical methodologies, volume 39, Bank for International Settlements.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Garidzirai Rufaro & Muzindutsi Paul-Francois, 2020. "A Panel ARDL Analsis of the Productivity of Key Economic Sectors Contributing to Local Economic Growth in an Emerging Country," Studia Universitatis Babeș-Bolyai Oeconomica, Sciendo, vol. 65(1), pages 39-53, April.

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Hyndman, Rob J. & Ahmed, Roman A. & Athanasopoulos, George & Shang, Han Lin, 2011. "Optimal combination forecasts for hierarchical time series," Computational Statistics & Data Analysis, Elsevier, vol. 55(9), pages 2579-2589, September.
    2. James Mitchell & Richard J. Smith & Martin R. Weale, 2013. "Efficient Aggregation Of Panel Qualitative Survey Data," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 28(4), pages 580-603, June.
    3. Martín Almuzara & Dante Amengual & Gabriele Fiorentini & Enrique Sentana, 2022. "GDP Solera. The Ideal Vintage Mix," Working Papers wp2022_2204, CEMFI.
    4. Chiara Bentivogli & Tommaso Ferraresi & Paola Monti & Renato Paniccià & Stefano Rosignoli, 2019. "Italian Regions in Global Value Chains: An Input-Output Approach," Politica economica, Società editrice il Mulino, issue 1, pages 55-94.
    5. Xianming Meng & Anthony Chin & Bligh Grant, 2015. "Long-run Effect of the Global Financial Crisis on Singapore's Tourism and the Economy," Asian Economic Journal, East Asian Economic Association, vol. 29(1), pages 41-60, March.
    6. Nicholas Crafts, 2021. "The Sources Of British Economic Growth Since The Industrial Revolution: Not The Same Old Story," Journal of Economic Surveys, Wiley Blackwell, vol. 35(3), pages 697-709, July.
    7. Frits Bos, 2009. "The Art And Craft Of Compiling National Accounts Statistics And Their Implications For Reliability," Review of Income and Wealth, International Association for Research in Income and Wealth, vol. 55(4), pages 930-958, December.
    8. Gesualdo, Maria & Rosignoli, Stefano, 2013. "Building a computable general equilibium model (cge) on a regional sam: the case of Tuscany," MPRA Paper 81412, University Library of Munich, Germany.
    9. Han Lin Shang, 2017. "Reconciling Forecasts of Infant Mortality Rates at National and Sub-National Levels: Grouped Time-Series Methods," Population Research and Policy Review, Springer;Southern Demographic Association (SDA), vol. 36(1), pages 55-84, February.
    10. Tucker McElroy, 2018. "Seasonal adjustment subject to accounting constraints," Statistica Neerlandica, Netherlands Society for Statistics and Operations Research, vol. 72(4), pages 574-589, November.
    11. Ton de Waal & Arnout van Delden & Sander Scholtus, 2020. "Multi‐source Statistics: Basic Situations and Methods," International Statistical Review, International Statistical Institute, vol. 88(1), pages 203-228, April.
    12. James Mitchell & Gary Koop & Stuart McIntyre & Aubrey Poon, 2020. "Reconciled Estimates of Monthly GDP in the US," Economic Statistics Centre of Excellence (ESCoE) Discussion Papers ESCoE DP-2020-16, Economic Statistics Centre of Excellence (ESCoE).
    13. Canning, Patrick & Wang, Zhi, 2004. "A flexible modeling framework to estimate interregional trade patterns and input-output accounts," Policy Research Working Paper Series 3359, The World Bank.
    14. Baoline Chen & Tommaso Di Fonzo & Thomas Howells & Marco Marini, 2018. "The statistical reconciliation of time series of accounts between two benchmark revisions," Statistica Neerlandica, Netherlands Society for Statistics and Operations Research, vol. 72(4), pages 533-552, November.
    15. K. Vela Velupillai, 2012. ""Dear Professor Mankiw..."- Reflections on Four Decades of Learning and Teaching Macroeconomics," ASSRU Discussion Papers 1206, ASSRU - Algorithmic Social Science Research Unit.
    16. Ehsan Khoman & James Mitchell & Martin Weale, 2008. "Incidence‐based estimates of life expectancy of the healthy for the UK: coherence between transition probabilities and aggregate life‐tables," Journal of the Royal Statistical Society Series A, Royal Statistical Society, vol. 171(1), pages 203-222, January.
    17. A. M. P. Santos & R. Salvador & C. Guedes Soares, 2018. "A dynamic view of the socioeconomic significance of ports," Maritime Economics & Logistics, Palgrave Macmillan;International Association of Maritime Economists (IAME), vol. 20(2), pages 169-189, June.
    18. Pennings, Clint L.P. & van Dalen, Jan, 2017. "Integrated hierarchical forecasting," European Journal of Operational Research, Elsevier, vol. 263(2), pages 412-418.
    19. Arie ten Cate, 2012. "The identification of reporting accuracies from mirror data," CPB Discussion Paper 216, CPB Netherlands Bureau for Economic Policy Analysis.
    20. Jean-Charles BRICONGNE & Alessandro TURRINI & Peter PONTUCH, 2019. "Assessing House Prices: Insights from HouseLev, a Dataset of Price Level Estimates," LEO Working Papers / DR LEO 2675, Orleans Economics Laboratory / Laboratoire d'Economie d'Orleans (LEO), University of Orleans.

    More about this item

    Keywords

    institutional sector; national accounts; price; production account; value added; volume;
    All these keywords.

    JEL classification:

    • C33 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Models with Panel Data; Spatio-temporal Models
    • C82 - Mathematical and Quantitative Methods - - Data Collection and Data Estimation Methodology; Computer Programs - - - Methodology for Collecting, Estimating, and Organizing Macroeconomic Data; Data Access
    • E01 - Macroeconomics and Monetary Economics - - General - - - Measurement and Data on National Income and Product Accounts and Wealth; Environmental Accounts
    • E30 - Macroeconomics and Monetary Economics - - Prices, Business Fluctuations, and Cycles - - - General (includes Measurement and Data)

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:ecb:ecbsps:201614. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Official Publications (email available below). General contact details of provider: https://edirc.repec.org/data/emieude.html .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.